code: def main():
      parser = ArgumentParser()
  
      # General Options
      parser.add_argument(
          "-s",
          "--save",
          dest="save",
          default=None,
          help="Where to save plot instead of showing it?",
      )
      parser.add_argument(
          "-t",
          "--type",
          dest="task_type",
          default="classifier",
          choices=("classifier",),
          help="Type of dataset",
      )
      parser.add_argument(
          "--sparse",
          dest="sparse",
          default=False,
          action="store_true",
          help="dataset property",
      )
      prop = parser.add_mutually_exclusive_group(required=True)
      prop.add_argument(
          "--multilabel",
          dest="multilabel",
          default=False,
          action="store_true",
          help="dataset property",
      )
      prop.add_argument(
          "--multiclass",
          dest="multiclass",
          default=False,
          action="store_true",
          help="dataset property",
      )
      prop.add_argument(
          "--binary",
          dest="binary",
          default=False,
          action="store_true",
          help="dataset property",
      )
  
      args, unknown = parser.parse_known_args()
  
      props = {
          "sparse": args.sparse,
          "multilabel": args.multilabel,
          "multiclass": args.multiclass,
      }
      est_dict, preproc_dict = get_dict(
          task_type=args.task_type, **props
      )
  
      est_table = build_table(est_dict)
      preproc_table = build_table(preproc_dict)
  
      est_table = table_str % (
          caption_str % (args.task_type, str(props)),
          est_table,
      )
      preproc_table = table_str % (
          caption_str % ("feature_preprocessor", str(props)),
          preproc_table,
      )
  
      tex_doc = template_string % "\n".join([est_table, preproc_table])
      if args.save is None:
          print(tex_doc)
      else:
          fh = open(args.save, "w")
          fh.write(tex_doc)
          fh.close()
          proc = subprocess.Popen(
              shlex.split("pdflatex %s" % args.save)
          )
          proc.communicate()
          try:
              os.remove(args.save.replace(".tex", ".aux"))
              os.remove(args.save.replace(".tex", ".log"))
          except OSError:
              # This is fine
              pass
  
file_path: auto-sklearn/misc/create_hyperparameter_table.py
imports: from argparse import ArgumentParser
  from collections import OrderedDict
  import os
  import shlex
  import subprocess
  import ConfigSpace.hyperparameters
  import autosklearn.pipeline.classification
  import autosklearn.pipeline.regression
label_desc: Use image node_id 3 for calling a global function with example usage: main() without return types